Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data.

BACKGROUND: Microbiome analysis is becoming a standard component in many scientific studies, but also requires extensive quality control of the 16S rRNA gene sequencing data prior to analysis. In particular, when investigating low-biomass microbial environments such as human skin, contaminants distort the true microbiome sample composition and need to be removed bioinformatically. We introduce MicrobIEM, a novel tool to bioinformatically remove contaminants using negative controls. RESULTS: We benchmarked MicrobIEM against five established decontamination approaches in four 16S rRNA amplicon sequencing datasets: three serially diluted mock communities (108-103 cells, 0.4-80% contamination) with even or staggered taxon compositions and a skin microbiome dataset. Results depended strongly on user-selected algorithm parameters. Overall, sample-based algorithms separated mock and contaminant sequences best in the even mock, whereas control-based algorithms performed better in the two staggered mocks, particularly in low-biomass samples (≤ 106 cells). We show that a correct decontamination benchmarking requires realistic staggered mock communities and unbiased evaluation measures such as Youden's index. In the skin dataset, the Decontam prevalence filter and MicrobIEM's ratio filter effectively reduced common contaminants while keeping skin-associated genera. CONCLUSIONS: MicrobIEM's ratio filter for decontamination performs better or as good as established bioinformatic decontamination tools. In contrast to established tools, MicrobIEM additionally provides interactive plots and supports selecting appropriate filtering parameters via a user-friendly graphical user interface. Therefore, MicrobIEM is the first quality control tool for microbiome experts without coding experience.

Exploiting breakdown in nonhost effector-target interactions to boost host disease resistance.

Plants are resistant to most microbial species due to nonhost resistance (NHR), providing broad-spectrum and durable immunity. However, the molecular components contributing to NHR are poorly characterised. We address the question of whether failure of pathogen effectors to manipulate nonhost plants plays a critical role in NHR. RxLR (Arg-any amino acid-Leu-Arg) effectors from two oomycete pathogens, Phytophthora infestans and Hyaloperonospora arabidopsidis, enhanced pathogen infection when expressed in host plants (Nicotiana benthamiana and Arabidopsis, respectively) but the same effectors performed poorly in distantly related nonhost pathosystems. Putative target proteins in the host plant potato were identified for 64 P. infestans RxLR effectors using yeast 2-hybrid (Y2H) screens. Candidate orthologues of these target proteins in the distantly related non-host plant Arabidopsis were identified and screened using matrix Y2H for interaction with RxLR effectors from both P. infestans and H. arabidopsidis. Few P. infestans effector-target protein interactions were conserved from potato to candidate Arabidopsis target orthologues (cAtOrths). However, there was an enrichment of H. arabidopsidis RxLR effectors interacting with cAtOrths. We expressed the cAtOrth AtPUB33, which unlike its potato orthologue did not interact with P. infestans effector PiSFI3, in potato and Nicotiana benthamiana. Expression of AtPUB33 significantly reduced P. infestans colonization in both host plants. Our results provide evidence that failure of pathogen effectors to interact with and/or correctly manipulate target proteins in distantly related non-host plants contributes to NHR. Moreover, exploiting this breakdown in effector-nonhost target interaction, transferring effector target orthologues from non-host to host plants is a strategy to reduce disease.

Fusarium head blight resistance in European winter wheat: insights from genome-wide transcriptome analysis.

BACKGROUND: Fusarium head blight (FHB) is a devastating disease of wheat worldwide. Resistance to FHB is quantitatively controlled by the combined effects of many small to medium effect QTL. Flowering traits, especially the extent of extruded anthers, are strongly associated with FHB resistance. RESULTS: To characterize the genetic basis of FHB resistance, we generated and analyzed phenotypic and gene expression data on the response to Fusarium graminearum (Fg) infection in 96 European winter wheat genotypes, including several lines containing introgressions from the highly resistant Asian cultivar Sumai3. The 96 lines represented a broad range in FHB resistance and were assigned to sub-groups based on their phenotypic FHB severity score. Comparative analyses were conducted to connect sub-group-specific expression profiles in response to Fg infection with FHB resistance level. Collectively, over 12,300 wheat genes were Fusarium responsive. The core set of genes induced in response to Fg was common across different resistance groups, indicating that the activation of basal defense response mechanisms was largely independent of the resistance level of the wheat line. Fg-induced genes tended to have higher expression levels in more susceptible genotypes. Compared to the more susceptible non-Sumai3 lines, the Sumai3-derivatives demonstrated higher constitutive expression of genes associated with cell wall and plant-type secondary cell wall biogenesis and higher constitutive and Fg-induced expression of genes involved in terpene metabolism. Gene expression analysis of the FHB QTL Qfhs.ifa-5A identified a constitutively expressed gene encoding a stress response NST1-like protein (TraesCS5A01G211300LC) as a candidate gene for FHB resistance. NST1 genes are key regulators of secondary cell wall biosynthesis in anther endothecium cells. Whether the stress response NST1-like gene affects anther extrusion, thereby affecting FHB resistance, needs further investigation. CONCLUSION: Induced and preexisting cell wall components and terpene metabolites contribute to resistance and limit fungal colonization early on. In contrast, excessive gene expression directs plant defense response towards programmed cell death which favors necrotrophic growth of the Fg pathogen and could thus lead to increased fungal colonization.

COMPOSITUM 1 contributes to the architectural simplification of barley inflorescence via meristem identity signals.

Grasses have varying inflorescence shapes; however, little is known about the genetic mechanisms specifying such shapes among tribes. Here, we identify the grass-specific TCP transcription factor COMPOSITUM 1 (COM1) expressing in inflorescence meristematic boundaries of different grasses. COM1 specifies branch-inhibition in barley (Triticeae) versus branch-formation in non-Triticeae grasses. Analyses of cell size, cell walls and transcripts reveal barley COM1 regulates cell growth, thereby affecting cell wall properties and signaling specifically in meristematic boundaries to establish identity of adjacent meristems. COM1 acts upstream of the boundary gene Liguleless1 and confers meristem identity partially independent of the COM2 pathway. Furthermore, COM1 is subject to purifying natural selection, thereby contributing to specification of the spike inflorescence shape. This meristem identity pathway has conceptual implications for both inflorescence evolution and molecular breeding in Triticeae.

Arabidopsis shoot stem cells display dynamic transcription and DNA methylation patterns.

In plants, aerial organs originate continuously from stem cells in the center of the shoot apical meristem. Descendants of stem cells in the subepidermal layer are progenitors of germ cells, giving rise to male and female gametes. In these cells, mutations, including insertions of transposable elements or viruses, must be avoided to preserve genome integrity across generations. To investigate the molecular characteristics of stem cells in Arabidopsis, we isolated their nuclei and analyzed stage-specific gene expression and DNA methylation in plants of different ages. Stem cell expression signatures are largely defined by developmental stage but include a core set of stem cell-specific genes, among which are genes implicated in epigenetic silencing. Transiently increased expression of transposable elements in meristems prior to flower induction correlates with increasing CHG methylation during development and decreased CHH methylation, before stem cells enter the reproductive lineage. These results suggest that epigenetic reprogramming may occur at an early stage in this lineage and could contribute to genome protection in stem cells during germline development.

Revealing the Venomous Secrets of the Spider's Web.

Orb-weaving spiders use a highly strong, sticky and elastic web to catch their prey. These web properties alone would be enough for the entrapment of prey; however, these spiders may be hiding venomous secrets in the web, which current research is revealing. Here, we provide strong proteotranscriptomic evidence for the presence of toxin/neurotoxin-like proteins, defensins, and proteolytic enzymes on the web silk from Nephila clavipes spider. The results from quantitative-based transcriptomic and proteomic approaches showed that silk-producing glands produce an extensive repertoire of toxin/neurotoxin-like proteins, similar to those already reported in spider venoms. Meanwhile, the insect toxicity results demonstrated that these toxic components can be lethal and/or paralytic chemical weapons used for prey capture on the web, and the presence of fatty acids in the web may be a responsible mechanism opening the way to the web toxins for accessing the interior of prey's body, as shown here. Comparative phylogenomic-level evolutionary analyses revealed orthologous genes among two spider groups, Araneomorphae and Mygalomorphae, and the findings showed protein sequences similar to toxins found in the taxa Scorpiones and Hymenoptera in addition to Araneae. Overall, these data represent a valuable resource to further investigate other spider web toxin systems and also suggest that N. clavipes web is not a passive mechanical trap for prey capture, but it exerts an active role in prey paralysis/killing using a series of neurotoxins.

Skin pH-dependent Staphylococcus aureus abundance as predictor for increasing atopic dermatitis severity.

BACKGROUND: Atopic eczema (atopic dermatitis, AD) is characterized by disrupted skin barrier associated with elevated skin pH and skin microbiome dysbiosis, due to high Staphylococcus aureus loads, especially during flares. Since S aureus shows optimal growth at neutral pH, we investigated the longitudinal interplay between these factors and AD severity in a pilot study. METHOD: Emollient (with either basic pH 8.5 or pH 5.5) was applied double-blinded twice daily to 6 AD patients and 6 healthy (HE) controls for 8 weeks. Weekly, skin swabs for microbiome analysis (deep sequencing) were taken, AD severity was assessed, and skin physiology (pH, hydration, transepidermal water loss) was measured. RESULTS: Physiological, microbiome, and clinical results were not robustly related to the pH of applied emollient. In contrast to longitudinally stable microbiome in HE, S aureus frequency significantly increased in AD over 8 weeks. High S aureus abundance was associated with skin pH 5.7-6.2. High baseline S aureus frequency predicted both increase in S aureus and in AD severity (EASI and local SCORAD) after 8 weeks. CONCLUSION: Skin pH is tightly regulated by intrinsic factors and limits the abundance of S aureus. High baseline S aureus abundance in turn predicts an increase in AD severity over the study period. This underlines the importance and potential of sustained intervention regarding the skin pH and urges for larger studies linking skin pH and skin S aureus abundance to understand driving factors of disease progression.

Insights into the SAM Synthetase Gene Family and Its Roles in Tomato Seedlings under Abiotic Stresses and Hormone Treatments.

S-Adenosyl-L-methionine (SAM) is a key enzyme involved in many important biological processes, such as ethylene and polyamine biosynthesis, transmethylation, and transsulfuration. Here, the SAM synthetase (SAMS) gene family was studied in ten different plants (Arabidopsis, tomato, eggplant, sunflower, Medicago truncatula, soybean, rice, barley, Triticum urartu and sorghum) with respect to its physical structure, physicochemical characteristics, and post-transcriptional and post-translational modifications. Additionally, the expression patterns of SAMS genes in tomato were analyzed based on a real-time quantitative PCR assay and an analysis of a public expression dataset. SAMS genes of monocots were more conserved according to the results of a phylogenetic analysis and the prediction of phosphorylation and glycosylation patterns. SAMS genes showed differential expression in response to abiotic stresses and exogenous hormone treatments. Solyc01g101060 was especially expressed in fruit and root tissues, while Solyc09g008280 was expressed in leaves. Additionally, our results revealed that exogenous BR and ABA treatments strongly reduced the expression of tomato SAMS genes. Our research provides new insights and clues about the role of SAMS genes. In particular, these results can inform future functional analyses aimed at revealing the molecular mechanisms underlying the functions of SAMS genes in plants.

Defining biomarkers to predict symptoms in subjects with and without allergy under natural pollen exposure.

BACKGROUND: Pollen exposure induces local and systemic allergic immune responses in sensitized individuals, but nonsensitized individuals also are exposed to pollen. The kinetics of symptom expression under natural pollen exposure have never been systematically studied, especially in subjects without allergy. OBJECTIVE: We monitored the humoral immune response under natural pollen exposure to potentially uncover nasal biomarkers for in-season symptom severity and identify protective factors. METHODS: We compared humoral immune response kinetics in a panel study of subjects with seasonal allergic rhinitis (SAR) and subjects without allergy and tested for cross-sectional and interseasonal differences in levels of serum and nasal, total, and Betula verrucosa 1-specific immunoglobulin isotypes; immunoglobulin free light chains; cytokines; and chemokines. Nonsupervised principal component analysis was performed for all nasal immune variables, and single immune variables were correlated with in-season symptom severity by Spearman test. RESULTS: Symptoms followed airborne pollen concentrations in subjects with SAR, with a time lag between 0 and 13 days depending on the pollen type. Of the 7 subjects with nonallergy, 4 also exhibited in-season symptoms whereas 3 did not. Cumulative symptoms in those without allergy were lower than in those with SAR but followed the pollen exposure with similar kinetics. Nasal eotaxin-2, CCL22/MDC, and monocyte chemoattactant protein-1 (MCP-1) levels were higher in subjects with SAR, whereas IL-8 levels were higher in subjects without allergy. Principal component analysis and Spearman correlations identified nasal levels of IL-8, IL-33, and Betula verrucosa 1-specific IgG4 (sIgG4) and Betula verrucosa 1-specific IgE (sIgE) antibodies as predictive for seasonal symptom severity. CONCLUSIONS: Nasal pollen-specific IgA and IgG isotypes are potentially protective within the humoral compartment. Nasal levels of IL-8, IL-33, sIgG4 and sIgE could be predictive biomarkers for pollen-specific symptom expression, irrespective of atopy.

S100A4 mRNA-protein relationship uncovered by measurement noise reduction.

Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalization of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to the genetic instability and "splicing weakness" involved. Here, we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunohistochemistry (qIHC) was introduced as an experimental readout to fine-tune the normalization choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman's coefficient ρ = 0.72 (p = 0.006)). KEY MESSAGES: • RNA-seq identifies stable pairs of consecutive exons in a heterogeneous tumour. • Poly(A) RNA templates for RT-qPCR avoid bias from circRNA and rRNA deregulation. • HNRNPL is stably expressed across various cancer tissues and osteosarcoma. • Logit transformed qIHC score better associates with mRNA amount. • Quantification of minor S100A4 mRNA species requires poly(A) RNA templates and dPCR.

DNA methylation analysis in plants: review of computational tools and future perspectives.

Genome-wide DNA methylation studies have quickly expanded due to advances in next-generation sequencing techniques along with a wealth of computational tools to analyze the data. Most of our knowledge about DNA methylation profiles, epigenetic heritability and the function of DNA methylation in plants derives from the model species Arabidopsis thaliana. There are increasingly many studies on DNA methylation in plants-uncovering methylation profiles and explaining variations in different plant tissues. Additionally, DNA methylation comparisons of different plant tissue types and dynamics during development processes are only slowly emerging but are crucial for understanding developmental and regulatory decisions. Translating this knowledge from plant model species to commercial crops could allow the establishment of new varieties with increased stress resilience and improved yield. In this review, we provide an overview of the most commonly applied bioinformatics tools for the analysis of DNA methylation data (particularly bisulfite sequencing data). The performances of a selection of the tools are analyzed for computational time and agreement in predicted methylated sites for A. thaliana, which has a smaller genome compared to the hexaploid bread wheat. The performance of the tools was benchmarked on five plant genomes. We give examples of applications of DNA methylation data analysis in crops (with a focus on cereals) and an outlook for future developments for DNA methylation status manipulations and data integration.

De Novo Genome Assembly of a Plant-Associated Rhodococcus qingshengii Strain (RL1) Isolated from Eruca sativa Mill. and Showing Plant Growth-Promoting Properties.

Rhodococcus qingshengii RL1 was isolated from surface-sterilized leaves of Eruca sativa Mill. and shows plant growth-promoting (PGP) properties. The de novo genome assembly consists of one chromosome with 6,253,838 bp and two plasmids with 144,038 bp and 448,745 bp. Many genes could be identified reflecting its PGP potential.

A proteotranscriptomic study of silk-producing glands from the orb-weaving spiders.

Orb-weaving spiders can produce different silk fibers, which constitute outstanding materials characterized by their high strength and elasticity. Researchers have tried to reproduce the fibers of these proteins synthetically and/or by using recombinant DNA technology, but only a few of the natural physicochemical and biophysical properties have been obtained to date. Female orb-web-spiders present seven silk-glands, which synthesize the spidroins and a series of other proteins, which interact with the spidroins, resulting in silk fibers with notable physicochemical properties. Despite the recognized importance of the silk-glands for understanding how the fibers are produced and processed, the investigation of these glands is at a nascent stage. In the current study we present the assembled transcriptome of silk-producing glands from the orb-weaving spider Nephila clavipes, as well as develop a large-scale proteomic approach for in-depth analyses of silk-producing glands. The present investigation revealed an extensive repertoire of hitherto undescribed proteins involved in silk secretion and processing, such as prevention of degradation during the silk spinning process, transportation, protection against proteolytic autolysis and against oxidative stress, molecular folding and stabilization, and post-translational modifications. Comparative phylogenomic-level evolutionary analyses revealed orthologous genes among three groups of silk-producing organisms - (i) Araneomorphae spiders, (ii) Mygalomorphae spiders, and (iii) silk-producing insects. A common orthologous gene, which was annotated as silk gland factor-3 is present among all species analysed. This protein belongs to a transcription factor family, that is important and related to the development of the silk apparatus synthesis in the silk glands of silk-producing arthropods.

Analysis of gene expression in rheumatoid arthritis and related conditions offers insights into sex-bias, gene biotypes and co-expression patterns.

The era of next-generation sequencing has mounted the foundation of many gene expression studies. In rheumatoid arthritis research, this has led to the discovery of important candidate genes which offered novel insights into mechanisms and their possible roles in the cure of the disease. In the last years, data generation has outstripped data analysis and while many studies focused on specific aspects of the disease, a global picture of the disease is not yet accomplished. Here, we analyzed and compared a collection of gene expression information from healthy individuals and from patients suffering under different arthritis conditions from published studies containing the following clinical conditions: early and established rheumatoid arthritis, osteoarthritis and arthralgia. We show comprehensive overviews of this data collection and give new insights specifically on gene expression in the early stage, into sex-dependent gene expression, and we describe general differences in expression of different biotypes of genes. Many genes that are related to cytoskeleton changes (actin filament related genes) are differently expressed in early rheumatoid arthritis in comparison to healthy subjects; interestingly, eight of these genes reverse their expression ratio significantly between men and women compared early rheumatoid arthritis and healthy subjects. There are some slighter changes between men and woman between the conditions early and established rheumatoid arthritis. Another aspect are miRNAs and other gene biotypes which are not only promising candidates for diagnoses but also change their expression grossly in average at rheumatoid arthritis and arthralgia compared to the healthy condition. With a selection of intersecting genes, we were able to generate simple classification models to distinguish between healthy and rheumatoid arthritis as well as between early rheumatoid arthritis to other arthritides based on gene expression.

Systems Biology of Plant-Microbiome Interactions.

In natural environments, plants are exposed to diverse microbiota that they interact with in complex ways. While plant-pathogen interactions have been intensely studied to understand defense mechanisms in plants, many microbes and microbial communities can have substantial beneficial effects on their plant host. Such beneficial effects include improved acquisition of nutrients, accelerated growth, resilience against pathogens, and improved resistance against abiotic stress conditions such as heat, drought, and salinity. However, the beneficial effects of bacterial strains or consortia on their host are often cultivar and species specific, posing an obstacle to their general application. Remarkably, many of the signals that trigger plant immune responses are molecularly highly similar and often identical in pathogenic and beneficial microbes. Thus, it is unclear what determines the outcome of a particular microbe-host interaction and which factors enable plants to distinguish beneficials from pathogens. To unravel the complex network of genetic, microbial, and metabolic interactions, including the signaling events mediating microbe-host interactions, comprehensive quantitative systems biology approaches will be needed.

Polyclonal symbiont populations in hydrothermal vent tubeworms and the environment.

Horizontally transmitted symbioses usually house multiple and variable symbiont genotypes that are acquired from a much more diverse environmental pool via partner choice mechanisms. However, in the deep-sea hydrothermal vent tubeworm Riftia pachyptila (Vestimentifera, Siboglinidae), it has been suggested that the Candidatus Endoriftia persephone symbiont is monoclonal. Here, we show with high-coverage metagenomics that adult R. pachyptila house a polyclonal symbiont population consisting of one dominant and several low-frequency variants. This dominance of one genotype is confirmed by multilocus gene sequencing of amplified housekeeping genes in a broad range of host individuals where three out of four loci ( atpA, uvrD and recA) revealed no genomic differences, while one locus ( gyrB) was more diverse in adults than in juveniles. We also analysed a metagenome of free-living Endoriftia and found that the free-living population showed greater sequence variability than the host-associated population. Most juveniles and adults shared a specific dominant genotype, while other genotypes can dominate in few individuals. We suggest that although generally permissive, partner choice is selective enough to restrict uptake of some genotypes present in the environment.

A Simple Method to Determine Cytotoxicity of Water-Soluble Organic Compounds and Solid Particles from Biomass Combustion in Lung Cells in Vitro.

Adverse health effects of condensable organic compounds (COC) and potential secondary organic aerosols from wood combustion emissions are difficult to determine. Hence, available information is usually limited to a small number of specific applications. Therefore, we introduced a simple, fast, and economic method where water-soluble COC (WSCOC) and WSCOC together with water-soluble primary solid particles (WSpSP) from wood combustion were sampled and subsequently exposed to cultured human lung cells. Comparing the cell viability of H187 human epithelial lung cells from five combustion devices, operated at different combustion conditions, no, or only a minor, cytotoxicity of WSCOC is found for stationary conditions in a grate boiler, a log wood boiler, and a pellet boiler. All combustion conditions in a log wood stove and unfavorable conditions in the other devices induce, however, significant cytotoxicity (median lethal concentration LC50 5-17 mg/L). Furthermore, a significant correlation between CO and cytotoxicity was found ( R2 ∼ 0.8) suggesting that the simply measurable gas phase compound CO can be used as a first indicator for the potential harmfulness of wood combustion emissions. Samples containing WSCOC plus WSpSP show no additional cytotoxicity compared to samples with COC only, indicating that WSCOC exhibit much higher cytotoxicity than WSpSP.

Effect of Stove Technology and Combustion Conditions on Gas and Particulate Emissions from Residential Biomass Combustion.

We have systematically examined the gas and particle phase emissions from seven wood combustion devices. Among total carbon mass emitted (excluding CO2), CO emissions were dominant, together with nonmethane volatile organic compounds (NMVOCs) (10-40%). Automated devices emitted 1-3 orders of magnitude lower CH4 (0.002-0.60 g kg-1 of wood) and NMVOCs (0.01-1 g kg-1 of wood) compared to batch-operated devices (CH4: 0.25-2.80 g kg-1 of wood; NMVOCs: 2.5-19 g kg-1 of wood). 60-90% of the total NMVOCs were emitted in the starting phase of batch-operated devices, except for the first load cycles. Partial-load conditions or deviations from the normal recommended operating conditions, such as use of wet wood/wheat pellets, oxygen rich or deficit conditions, significantly enhanced the emissions. NMVOCs were largely dominated by small carboxylic acids and alcohols, and furans. Despite the large variability in NMVOCs emission strengths, the relative contribution of different classes showed large similarities among different devices and combustion phases. We show that specific improper operating conditions may even for advanced technology not result in the emission reduction of secondary organic aerosol (SOA) forming compounds and thus not reduce the impact of wood combustion on climate and health.

BioSankey: Visualization of Microbial Communities Over Time.

Metagenomics provides quantitative measurements for microbial species over time. To obtain a global overview of an experiment and to explore the full potential of a given dataset, intuitive and interactive visualization tools are needed. Therefore, we established BioSankey to visualize microbial species in microbiome studies over time as a Sankey diagram. These diagrams are embedded into a project-specific webpage which depends only on JavaScript and Google API to allow searches of interesting species without requiring a web server or connection to a database. BioSankey is a valuable tool to visualize different data elements from single or dual RNA-seq datasets and additionally enables a straightforward exchange of results among collaboration partners.

miR172 downregulates the translation of cleistogamy 1 in barley.

Background and Aims: Floret opening in barley is induced by the swelling of the lodicule, a trait under the control of the cleistogamy1 (cly1) gene. The product of cly1 is a member of the APETALA2 (AP2) transcription factor family, which inhibits lodicule development. A sequence polymorphism at the miR172 target site within cly1 has been associated with variation in lodicule development and hence with the cleistogamous phenotype. It was unclear whether miR172 actually functions in cly1 regulation and, if it does, which miR172 gene contributes to cleistogamy. It was also interesting to explore whether miR172-mediated cly1 regulation occurs at transcriptional level or at translational level. Methods: Deep sequencing of small RNA identified the miR172 sequences expressed in barley immature spikes. miR172 genes were confirmed by computational and expression analysis. miR172 and cly1 expression profiles were determined by in situ hybridization and quantitative expression analysis. Immunoblot analysis provided the CLY1 protein quantifications. Definitive evidence of the role of miR172 in cleistogamy was provided by a transposon Ds-induced mutant of Hv-miR172a. Key Results: A small RNA analysis of the immature barley spike revealed three isomers, miR172a, b and c, of which miR172a was the most abundant. In situ hybridization analysis showed that miR172 and cly1 co-localize in the lodicule primordium, suggesting that these two molecules potentially interact with one another. Immunoblot analysis showed that the sequence polymorphism at the miR172 target site within cly1 reduced the abundance of the CLY1 protein, but not that of its transcript. In a Ds-induced mutant of Hv-miR172a, which generates no mature miR172a, the lodicules fail to grow, resulting in a very small lodicule. Conclusions: Direct evidence is presented to show that miR172a acts to reduce the abundance of the CLY1 protein, which enables open flowering in barley.